کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
379411 | 659299 | 2007 | 18 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Privacy-preserving distributed association rule mining via semi-trusted mixer
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی کامپیوتر
هوش مصنوعی
پیش نمایش صفحه اول مقاله
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چکیده انگلیسی
Distributed data mining applications, such as those dealing with health care, finance, counter-terrorism and homeland defence, use sensitive data from distributed databases held by different parties. This comes into direct conflict with an individual’s need and right to privacy. In this paper, we come up with a privacy-preserving distributed association rule mining protocol based on a new semi-trusted mixer model. Our protocol can protect the privacy of each distributed database against the coalition up to n − 2 other data sites or even the mixer if the mixer does not collude with any data site. Furthermore, our protocol needs only two communications between each data site and the mixer in one round of data collection.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Data & Knowledge Engineering - Volume 63, Issue 2, November 2007, Pages 550–567
Journal: Data & Knowledge Engineering - Volume 63, Issue 2, November 2007, Pages 550–567
نویسندگان
Xun Yi, Yanchun Zhang,